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SAGE

SAGE

by PsYcGoD
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Python
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sage_suggest_fix

After a SAGE command fails, get safe fix suggestions with explanations and confidence scores without executing any commands.

Instructions

Suggest safe next steps for a failed SAGE command. Use after sage_explain_error when you want possible fixes but do not want them executed automatically. Returns a list of fix suggestions with explanation, confidence, and candidate command when available. Read-only: it never applies patches and never runs the suggested command.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "sage_suggest_fix"
  }
}

Input Schema

NameRequiredDescriptionDefault
command_idNoOptional SAGE run id. Omit to use the most recent failed command.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.5.8
  2. Removedv2.5.1
  3. Changed2 schema fields changedv2.4.22
    • changedInput schema / properties / command_id / description
      Previous value: -"Specific command ID (optional, defaults to last failed)"New value: +"Optional SAGE run id. Omit to use the most recent failed command."
    • addedInput schema / properties / command_id / minimum
      Added value: +1
  4. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It clearly states the tool is read-only and never applies patches or runs commands, which covers key safety behavior. However, it doesn't mention error handling or response details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise: three sentences front-loading purpose, usage, return value, and safety. Every sentence adds value with no redundancy or unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has one optional parameter, no output schema, and simple behavior, the description covers all essential aspects: purpose, usage context, return structure, and safety. It is complete for an AI agent to select and invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, with the schema already describing the optional command_id parameter and its default behavior. The description adds no additional parameter information, so baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool suggests safe next steps for a failed SAGE command, using a specific verb and resource. It distinguishes itself from siblings like sage_explain_error and sage_run_workflow by specifying when to use it and what it does.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly advises to use after sage_explain_error when possible fixes are wanted without execution. It also clarifies that it is read-only and never applies patches, setting clear expectations and alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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